System and method for rating plural products

ABSTRACT

A system and method for rating of each of plural products comprising identifying plurality of attributes associated with a category of product, applying a scalar structure for each attribute to provide scalar value of each attribute for each of the plural products, determining an incremental competitive index for each attribute of each product based on the scalar value of each attribute and a number of products having the scalar value, and rating each product based on the determined competitive index.

CROSS-REFERENCES TO RELATED APPLICATION

This application is a Continuation of U.S. patent application Ser. No.14/262,049, filed Apr. 25, 2014 (now pending), which is a Continuationof U.S. patent application Ser. No. 13/298,085, filed Nov. 16, 2011, nowU.S. Pat. No. 8,751,331, issued Jun. 10, 2014, which is a Continuationof U.S. patent application Ser. No. 12/217,095, filed Jul. 1, 2008, nowU.S. Pat. No. 8,082,214, issued Dec. 20, 2011, which is a Divisional ofU.S. patent application Ser. No. 10/265,189, filed Oct. 7, 2002, nowU.S. Pat. No. 7,627,486, issued Dec. 1, 2009, the disclosures of whichare hereby incorporated by reference in their entireties.

BACKGROUND OF THE INVENTION Field of the Invention

The present invention is directed to systems and methods for ratingplural products. In particular, the present invention is directed tosuch systems and methods that allow rating of plural products based ontheir attributes.

Description of Related Art

Many different models of products from many different manufacturers aregenerally available for each type or category of product. Typically,manufacturers of a particular category of product offer various modelsin their product line, each model targeting a particular group of usersand/or meeting the specific needs of a market segment. For instance,manufacturers of automobiles, vacuum cleaners, cameras, computers, etc.all generally manufacture a variety of models of their products. In manyinstances, each model from each manufacturer and models from differingmanufacturers have different features and/or attributes associated withthe particular category of product.

For example, in the product category of vacuum cleaners, various modelshaving different combinations of features and/or attributes arepresently available. These features and/or attributes for vacuumcleaners include bag/bagless operation, motor power, attachments,exhaust filtration, price, etc. One particular model of a vacuum cleanermay have a bag to collect debris, a 6 ampere motor, without attachmentsor exhaust filtration and be typically sold in the marketplace for $60U.S. Another particular model of a vacuum cleaner may have a baglesscompartment to collect debris, an 8 ampere motor, provided withattachments and a HEPA filtration, and be typically sold in themarketplace for $160 U.S. Of course, many other features and attributesmay distinguish each of the vacuum cleaners that are available.

In another example, for the product category of digital cameras,features and/or attributes include optical and digital zoom capability,pixel count, the presence, type and size of a view screen, flashcapacity, memory capacity, price, etc. One particular model of digitalcamera may have a 2× optical zoom, 2.1 megapixels, a flash, a 2 inchcolor view screen, a 32 Mb memory, and be typically sold in the marketplace for $200 U.S. Another particular model of digital camera may havea 3× digital zoom, 4 megapixels, a flash, a 3 inch color view screen, a64 Mb memory and be typically sold in the market place for $400 U.S. Ofcourse, many other features and attributes may distinguish each of thedigital cameras that are available in the digital camera productcategory.

The vast number of manufacturers and models available for each productcategory, and the disparity in features and/or attributes between theproducts of a category can make a consumer's purchasing decision verydifficult. Companies such as CNET Networks, Inc. (herienafter “CNET”)which operates www.cnet.com provide information regarding consumer andtechnology oriented products such as electronics and computer productsfor buyers, sellers, and suppliers of technology, as well as any otherinterested user. In addition to providing raw data and information, manydifferent products in a particular product category are evaluated byeditors of CNET for various features and/or attributes and rated on ascale of 1 through 10. Products that are evaluated to have higherquality and to provide superior value to consumers are rated higher thanproducts of lesser quality and value. The information provided by CNETand others regarding various products of a product category may be usedby consumers to facilitate potential purchase decisions. However, theprocess of rating the numerous products is time and labor intensiverequiring trained individuals familiar with features and/or attributesof a product category to evaluate each of the products. In addition, asexpected, this requirement significantly increases costs associated withproviding such ratings. Further, such rating processes can be highlysubjective.

Various automated systems have been developed to eliminate orsubstantially reduce the requirement for individual evaluation of eachproduct. For instance, U.S. Pat. No. 5,731,991 to Kinra et al. disclosesa system for evaluating a software product including an interface thatreceives product data relating to the software product, a first memorythat stores the product data, and a second memory that stores aplurality of weighting values. The system also includes a processor thatis coupled to the first memory and the second memory which applies theplurality of weighting values to the product data to generate at leastone criterion score for the software product, each criterion scorerepresenting an evaluation of the software product.

U.S. Pat. No. 6,236,990 to Geller et al. discloses a system and methodfor assisting a user in selecting a product from multiple products thatare grouped into categories. The reference discloses that informationsuch as attributes about the products of each category, and questionsrelated to the attributes, are received and stored. In addition,possible user's responses to the questions and weights associated witheach possible response are also received and stored. Evaluation ratingsfor each of the attributes of each of the products are also received andstored. The reference discloses that the user selects a category and isprovided with questions corresponding to the attributes of the productsin the category selected. For each product in the category, a productscore is calculated by summing the product of the weights of theresponses by the evaluation ratings for that product. The results aredisplayed organized in rows and columns in the order of the productscores and weights. The reference further discloses that the user maychange the weights, change categories, or obtain additional informationabout each product. In addition, the reference further discloses thatthe system allows attribution of the evaluation ratings, and may placean order for some or all products.

SUMMARY OF THE INVENTION

A first aspect of the present invention is a method for rating each ofplural products comprising the steps of identifying plurality ofattributes associated with a category of product, applying a scalarstructure for each attribute to provide scalar value of each attributefor each of the plural products, determining an incremental competitiveindex for each attribute of each product based on the scalar value ofeach attribute and a number of products having the scalar value, andrating each product based on the determined competitive index.

A second aspect of the present invention is a method for rating pluralproducts is provided comprising the steps of identifying plurality ofattributes associated with a category of product, the plurality ofattributes including price of each of the plural products, applying ascalar structure for each attribute to provide scalar value of eachattribute for each of the plural products, and determining anincremental index for each attribute of each product based on the scalarvalue of each attribute. Price offset of each product based on anaverage price of the plural products in the category is determined andapportioned to one or more attribute associated with the category. Theapportioned price offsets are correlated to increments of incrementalindex. A theoretical value price of each product is determined based onthe correlated apportioned priced offsets, and the plural products arerated based on actual product price and the determined theoretical valueprice.

A third aspect of the present invention is a rating system for ratingeach of plural products is provided, the system comprising anidentification module that stores plurality of attributes associatedwith a category of product, a quantification module adapted to apply ascalar structure for each attribute to provide scalar value of eachattribute for each of the plural products, a competitive indexing modulethat determines an incremental competitive index for each attribute ofeach product based on the scalar value of each attribute and number ofproducts having the scalar value, and a product rating module that rateseach product based on the determined competitive index.

A fourth aspect of the present invention is a rating system for ratingplural products is provided comprising an identification module thatstores plurality of attributes associated with a category of product,the plurality of attributes including price of each of the pluralproducts, a quantification module adapted to apply a scalar structurefor each attribute to provide scalar value of each attribute for each ofthe plural products, and an indexing module that determines anincremental index for each attribute of each product based on the scalarvalue of each attribute. The system also includes a price offset modulethat determines price offset of each product based on an average priceof the plural products in the category, and apportions the price offsetof each product to one or more attribute associated with the category ofproduct. A valuation module then determines a theoretical value price ofeach product based on the correlated apportioned priced offsets, and aproduct rating module that rates each product based on actual productprice and the determined theoretical value price.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a schematic illustration of a system for rating pluralproducts in accordance with one embodiment of the present invention.

FIG. 2 is a flow chart of a method for rating plural products inaccordance with one embodiment of the present invention.

FIG. 3 is a flow chart of a method for rating plural products inaccordance with another embodiment of the present invention.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENT

Conventional rating systems and methods possess various disadvantagesthat limit their utility and accuracy. In particular, the most commonlyused rating method is based on percentile rank which is defined as thepercentage of items in the data set which are below a value in question.Two problems arise with the use of percentile rank in rating products ofa product category.

Firstly, by definition, the average percentile rank is not guaranteed tobe 0.50. In fact, the average percentile rank actually moves around asthe data changes. This makes it difficult to generate a balanced indexfrom percentile-ranked values that rates products accurately relative toother products in a product category without continual re-normalizationof the index.

Secondly, percentile rank does not provide an accurate determination oftop and bottom index values indicative of the feature and/or attributein situations where the number of possible values is small, forinstance, when the index values range merely from 0 to 1 or 0 to 3. Inthis regard, the percentile rank methods assign zero for the bottomindex value, regardless of how common or how rare it is for an item tohave such a feature and/or attribute corresponding to the index value.Referring to the example noted previously, if nearly all digital camerasin the market lack a certain attribute and/or feature, a zero percentilerank is assigned to these products with respect to the certain attributeand/or feature that is missing. Likewise, if most digital cameras have aparticular attribute and/or feature, and only one camera lacks thatfeature, a zero percentile rank is assigned to this product.

Thus, conventional methods for rating products which utilize percentilerank do not differentiate between features and/or attributes which arepresent or missing from a large majority of products from featuresand/or attributes which are present or missing from a small minority ofproducts. However, lacking a feature which nearly all competitors have,is usually perceived by consumers as being significantly worse thanlacking a feature which is hard to find. Therefore, a significantdisadvantage of conventional systems and methods for rating products isthat they do not rate or rank products while taking into considerationthe actual number of products in a product category that have, or do nothave, a particular feature and/or attribute.

The preferred embodiment described below facilitates rating pluralproducts without the disadvantages of conventional methods and systemsfor rating. The preferred embodiment facilitates rating plural productswhile taking into consideration the actual number of products in aproduct category that have, or do not have, a particular feature and/orattribute. In the preferred embodiment, the average index can be 0.50without re-normalization of the index.

FIG. 1 is a schematic illustration of a rating system 10 for ratingplural products in accordance with one embodiment of the presentinvention. Whereas the present invention may be applied using theconventional percentile rank, it will be evident from the discussionbelow that the preferred embodiment of the present invention provides arating system which takes into consideration the actual number ofproducts in a product category that have, or do not have, a particularfeature and/or attribute. For clarity purposes, the present invention isalso described below as applied to rating digital cameras. However, itshould be evident that the present invention may be readily used to rateany products of any other product category, and rating of digitalcameras is merely provided as one example.

In accordance with the illustrated embodiment of the present invention,the rating system 10 is provided with a central processing unit 12(hereinafter “CPU”) which is adapted to control and/or facilitatefunctions of various modules of the rating system 10 as described indetail below. It should be initially noted that the rating system 10 ofFIG. 1 may be implemented with any type of hardware and software, andmay be a pre-programmed general purpose computing device. For example,the rating system 10 may be implemented using a personal computer, aportable computer, a thin client, a hand held device, a wireless phone,or any combination of such devices. The rating system 10 may be a singledevice at a single location or multiple devices at a single, ormultiple, locations that are connected together using any appropriatecommunication protocols over any communication medium such as electriccable, fiber optic cable, any other cable, or in a wireless manner usingradio frequency, infrared, or other technologies.

It should also be noted that the rating system 10 in accordance with oneembodiment of the present invention is illustrated and discussed hereinas having a plurality of modules which perform particular functions. Itshould be understood that these modules are merely schematicallyillustrated based on their function for clarity purposes only, and donot necessary represent specific hardware or software. In this regard,these modules may be hardware and/or software implemented andsubstantially perform the particular functions explained. Moreover, twoor more of these modules may be combined together within the ratingsystem 10, or divided into more modules based on the particular functiondesired. Thus, the present invention as schematically embodied in FIG. 1should not be construed to limit the rating system 10 of the presentinvention.

In the illustrated embodiment, the rating system 10 is connected to anetwork 14 that allows publishing and remote access to the rating system10. The network 14 may be any type of communications channel, such asthe Internet, a local area network (LAN), a wide area network (WAN),direct computer connections, and may be accomplished in a wirelessmanner using radio frequency, infrared, or other technologies, using anytype of communication hardware and protocols. The specific details ofthe above devices and technology referenced are well known in the artand thus omitted herein.

The rating system 10 includes an identification module 16 that storesplurality of attributes associated with a category of product. The“attributes” as used and referred to herein collectively refer toparticular features and/or characteristics of a product or productcategory. For instance, as previously described, attributes for adigital camera category may include optical and digital zoom, pixelsize, presence and size of a view screen, flash capacity, memorycapacity, price, etc. In one embodiment of the present invention, anautomated crawler or search engine may be used to gather the attributesfor a product category as well as the attributes of each product. Ofcourse, such information may also be gathered manually. Theidentification module 16 then stores the gathered attributes for aproduct category and the attributes of each product in a database orother storage device (not shown). Preferably, the plurality ofattributes that is used to rate the products of a given categoryincludes the price of each of the plural products. In addition, otherpertinent data may be gathered and stored by the identification modulesuch as merchants that are selling the product.

The rating system 10 also includes a quantification module 18 that isadapted to apply a scalar structure for each attribute to provide ascalar value of each attribute for each of the plural products. In otherwords, scalar variables are applied to quantify the attribute of eachproduct so that the information stored in the identification module 16may be processed. For example, whether a digital camera is provided witha view screen or not, and the type and size of the view screen, ifprovided, should all preferably be numerically represented.

Numerous types of scalar structures may be used. For example, a booleanstructure may be used where False=0 and True=1. Alternatively, anextended boolean structure may be used where False=0, Optional=1, andIncluded=2. In still another alternative, a discrete structure may beused. In the example of digital cameras, the attribute of a view screenmay be provided with scalar values where NoScreen=0, LCD=1,BackLitLCD=2, ColorLCD=3, etc. Of course, these structures are merelyprovided as examples of how a scalar structure for each attribute may beapplied to provide a scalar value of each attribute for each of theplural products. In addition, other attributes of a product category maybe already numeric so that the numeric values of the attributes may beutilized directly. For example, the number of pixels of a digital camerais described as a numeral such as 2.1 megapixels, which may be directlyused instead of applying a particular scalar structure thereto. Itshould also be noted that such numeric attributes should be normalizedso that same units of measure are used, for instances, the size of theview screen for all digital cameras should be in the same units, such asinches.

The rating system 10 in accordance with the illustrated embodiment alsoincludes an indexing module 20 that determines an incremental index foreach attribute of each product, based on the scalar value of eachattribute, as applied by the quantification module 18 discussed above.Although the incremental index may be a percentile rank, the incrementalindex is preferably a competitive index which compensates for the numberof products in a product category that have the particular scalar value(which represents a particular attribute). In the present embodiment,the indexing module 20 determines the incremental index for eachattribute by calculating a percentile rank of each scalar value. Then,the indexing module 20 calculates the percentile rank range which eachscalar value spans. The indexing module 20 then processes a maximumpercentile rank and a minimum percentile rank of the calculatedpercentile rank range. In accordance with one embodiment, the indexingmodule 20 processes the maximum percentile rank and the minimumpercentile rank by calculating an average of the maximum and the minimumpercentile rank. Alternatively, or in addition thereto, the competitiveindexing module 20 may also sequence the scalar value of each attributefor each of the plural products.

The above described “competitive index” is further explained by theexample of TABLE 1 discussed below which illustrates how the indexingmodule 20 determines the incremental index, which in this particularexample, is the competitive index. As previously noted, whereasconventional percentile rank may be used as the index, the competitiveindex is preferably used which provides significant advantages over theconventional percentile rank as will be evident in view of the exampleof TABLE 1, as well as the examples set forth in TABLE 2, and TABLE 3described in detail below.

In the example of TABLE 1, the scalar structure is applied for eachattribute for each of the plural products by the quantification module18. In particular, the scalar values may have a discrete structurerepresenting the presence and type of view screen in a digital camerawhere NoScreen=0, LCD=1, BackLitLCD=2, and ColorLCD=3. In the examplebelow, the scalar value of each attribute for each of the pluralproducts have been sequenced from high value 3 to low value 0. Moreover,TABLE 1 further shows in the column marked “Percentile Rank”, thecorresponding percentile rank that is used to calculate the competitiveindex. The percentile rank may be calculated in a conventional mannerfor the corresponding scalar values.

TABLE 1 View Screen Scalar Comparison of Values Percentile and SequencedCompetitive from high to Percentile Competitive Index low (10 total)Rank Index 3 0.9 0.95 2 0.7 0.8 2 0.7 0.8 1 0.3 0.5 1 0.3 0.5 1 0.3 0.51 0.3 0.5 0 0 0.15 0 0 0.15 0 0 0.15 Average 1.1 0.35 0.5

As previously described, the most commonly used rating method is basedon percentile rank which does not ensure that the average percentilerank is 0.50 thereby requiring continual re-normalization of the indexto provide accurate rating of a product relative to other products in aproduct category. In addition, as evident from examination of thecalculated percentile rank values, the conventional percentile rankmethod assigns zeroes for the bottom index value despite the fact thatthree of the products, or full 30% of the products, do not have thisattribute (i.e. in this example, has a scalar value of zero). Thus,conventional methods for rating products do not compensate for thenumber of products that have, or do not have, a particular attribute andthus do not reflect market realities.

In contrast, the competitive index as implemented in the presentembodiment compensates for the number of products that have, or do nothave, a particular attribute. The competitive index is calculated in thepresent embodiment by the indexing module 20 which determines thepercentile rank range which each scalar value spans. For instance, inthe example of Table 1, the scalar value “0” spans a 0-30 percentilerank range, the scalar value “1” spans a 30-70 percentile rank range,the scalar value “2” spans a 70-90 percentile rank range, and lastly,the scalar value “3” spans a 90-100 percentile rank range.

In accordance with the illustrated embodiment, the indexing module 20then processes the maximum percentile rank and a minimum percentile rankof the percentile rank ranges. In this regard, the indexing module 20processes the maximum percentile rank and the minimum percentile rank bycalculating an average of the numerical maximum percentile rank and thenumerical minimum percentile rank. Thus, in the present example of TABLE1, the corresponding competitive indexes are calculated as follows. Withrespect to the scalar value “0”, the numerical value of minimumpercentile rank of 0 and the maximum percentile rank of 0.30 areaveraged together to provide 0.15 as the competitive index. For thescalar value “1”, the numerical value of minimum percentile rank of 0.30and the maximum percentile rank of 0.70 are averaged together to provide0.50 as the competitive index. For scalar value “2”, the numerical valueof minimum percentile rank of 0.70 and the maximum percentile rank of0.90 are averaged together to provide 0.80 as the competitive index.With respect to the scalar value “3”, the numerical value of minimumpercentile rank of 0.90 and the maximum percentile rank of 1.00 areaveraged together to provide 0.95 as the competitive index.

The competitive index calculated in the manner described for the aboveexample maintains the average competitive index at 0.50 so that aproduct having a competitive index value above 0.50 for a particularattribute represents better-than-average product for that attribute, anda product having a competitive index values below 0.50 for anotherparticular attribute represents worse-than-average product for thatparticular attribute. It should be evident that the competitive indexcalculated in the above described manner compensates for the actualnumber of products in the product category that has, or does not have, aparticular attribute. For instance, in the present example, if 6products (out of 10) have the “0” scalar value instead of 3, thecompetitive index would change from 0.15 to 0.30. Of course, it shouldalso be noted that the competitive index may be calculated in adifferent manner as long as the calculated competitive index compensatesfor the actual number of products in the product category that has, ordoes not have, a particular attribute.

As previously noted, whereas the present invention may be implementedusing the conventional percentile rank, the above example illustratesthe advantages of using the competitive index for the preferredimplementation. The above noted characteristics of the competitive indexin accordance with one embodiment of the present invention and itsdistinction when compared to percentage rank are further highlighted inTABLE 2 shown below.

TABLE 2 Value Set A Value Set B Scalar Percentile Competitive ScalarPercentile Competitive Value Rank Index Value Rank Index 1 0.80 0.90 10.20 0.60 1 0.80 0.90 1 0.20 0.60 0 0.00 0.40 1 0.20 0.60 0 0.00 0.40 10.20 0.60 0 0.00 0.40 1 0.20 0.60 0 0.00 0.40 1 0.20 0.60 0 0.00 0.40 10.20 0.60 0 0.00 0.40 1 0.20 0.60 0 0.00 0.40 0 0.00 0.10 0 0.00 0.40 00.00 0.10

Table 2 shows two sets of values, “Value Set A”, and “Value Set B” thatset forth scalar values of ten products for a particular attribute ofthe product's category in columns indicated “Scalar Value”, and theircorresponding percentile rank and calculated competitive index incolumns indicated “Percentile Rank” and “Competitive Index”,respectively. As shown, in both value sets, the scalar values wereintentionally chosen to span a very narrow range, i.e. between 0 and 1.In addition, the majority of products in Value Set A have the scalarvalue of 0 while the majority of products in Value Set B have the scalarvalue of 1 to show how the competitive index compensates for thedistribution of the scalar values. In particular, eight of the productshave the scalar value of 0 and two of the products have the scalar valueof 1 in Value Set A, whereas only two of the products have the scalarvalue of 0 and eight of the products have the scalar value of 1 in ValueSet B.

From carefully reviewing TABLE 2, it can be seen that for scalar valueof 1 in Value Set A, the competitive index calculated in the mannerdescribed above is nearly the same as the conventional percentile rank.For the products having the scalar value of 1, the competitive index is0.90 while the percentile rank is 0.80. However, the competitive indexis significantly higher for products lacking that particular attribute,i.e. having a scalar value of 0, as compared to the conventionalpercentile rank. In particular, the percentile rank is 0 for theproducts that have a scalar value of 0 thereby inaccurately giving theimpression that these products are at the very bottom of all theproducts with respect to the particular attribute, when in fact, theseproducts are average or typical. In contrast, the competitive index forthese products is 0.40 which is slightly below the average value of 0.50which more accurately reflects the fact that most items in thisparticular category, in this example, 8 out of 10 products, lack thatattribute.

In the quite different example set forth in Value Set B where it iscommon for most products to have a scalar value of 1 for the particularattribute, the conventional percentile rank is merely 0.20 which again,inaccurately gives the impression that products having the scalar valueof 1 are at the bottom of all the products with respect to theparticular attribute. In contrast, the competitive index calculated inthe manner previously described for these products is 0.60 which isslightly above the average of 0.50. This more accurately reflects thefact that most items in this particular category, in this example, 8 outof 10 products, have that attribute.

The disadvantage of conventional percentile rank is also clearly evidentby comparing the percentile rank of products having scalar value of 0 inValue Set A with those of Value Set B. As shown, conventional percentilerank treats these products with the scalar value of 0 the same in bothvalue sets regardless of the fact that most of the other products do nothave a particular attribute in Value Set A, while most of the otherproducts have a particular attribute in Value Set B. As described above,this does not correspond with how consumers are likely to evaluate theproducts in the market. In contrast, as also described above, thecompetitive index compensates for the number of products in a productcategory that have the particular scalar value and better correspondswith how consumers are likely to evaluate the products.

Furthermore, the competitive index also takes into consideration thefact that some increments of scalar value of a particular attribute maybe more meaningful to consumers than other increments. Thischaracteristic of competitive index is illustrated and described infurther detail relative to TABLE 3 below.

TABLE 3 Scalar Value for Resolution Competitive (Megapixels) index 60.95 5 0.85 3 0.70 3 0.70 2 0.35 2 0.35 2 0.35 2 0.35 2 0.35 1 0.05

TABLE 3 tabulates the attribute of resolution in digital cameras, i.e.the number of pixels. In the present example, each of the scalar valuescorrespond directly to the number of megapixels of the digital camera.Thus, the scalar value of 1 corresponds directly to a digital camerafeaturing 1 megapixels, the scalar value of 2 corresponds directly to adigital camera featuring 2 megapixels, and so forth with the scalarvalue of 6 corresponds directly to a digital camera featuring 6megapixels. Of course, in actuality, various digital cameras may featuredifferent number of megapixels, such as 1.2 megapixels, 2.1 megapixels,etc. However, for the purpose of this example, these values can berounded to provide whole increments for the scalar value.

It is well known in the digital camera market that with all otherattributes the same, the difference in value to a consumer between adigital camera featuring 2 megapixels versus 1 megapixels is far greaterthan the difference in value between a digital camera featuring 6megapixels versus 5 megapixels. Stated in another manner, the quality ofpictures captured by a digital camera featuring 2 megapixels issignificantly better than those captured by a digital camera featuring 1megapixels. However, the quality of pictures captured by a digitalcamera featuring 6 megapixels is only very marginally better than thosecaptured by a digital camera featuring 5 megapixels. This is merely theconcept of diminishing returns taking effect where each incrementalincrease in the scalar value, i.e. the incremental increase inmegapixels resolution, adds value to the digital camera, but this valueis added in decreasing amounts.

The above described non-linearity in value of the product versus theincremental increase in the scalar value is clearly reflected in thecalculated competitive rank which shows that the difference between thecompetitive indexes of a digital camera featuring 6 megapixels versus 5megapixels is significantly less than the difference between thecompetitive indexes of a digital camera featuring 2 megapixels versus 1megapixels. As indicated in TABLE 3, the competitive index of a digitalcamera featuring 6 megapixels is 0.95 while the competitive index of adigital camera featuring 5 megapixels is 0.85 thereby indicating adifference in competitive index of 0.1. In contrast, the competitiveindex of a digital camera featuring 2 megapixels is 0.35 while thecompetitive index of a digital camera featuring 1 megapixels is 0.05thereby indicating a difference in competitive index of 0.3 which issignificantly greater than 0.1. Thus, although in both cases, thedifferences between the digital cameras were 1 megapixels, thecorresponding difference in the competitive index were not the same. Infact, a 200% greater impact is realized in incrementally increasingresolution to 2 megapixels from 1 megapixels, as compared toincrementally increasing resolution to 6 megapixels from 5 megapixels.

Therefore, in view of the examples as set forth in TABLE 1, TABLE 2, andTABLE 3 described in detail above, it should now be evident that thecompetitive index compensates for the number of products in a productcategory that have the particular scalar value. It should also beevident that the competitive index better corresponds with how consumersare likely to evaluate the products as compared to the conventionalpercentile rank. Thus, whereas the present invention may be implementedutilizing percentile rank, it is preferably implemented utilizingcompetitive index instead.

It should also be noted that very precise and well distributed scalarvalues should de-granularized, for instance by rounding, to avoid havingthe percentile ranges be very narrow which would result in misleadingcompetitive indexes. Potential for such errors can be seen in TABLE 4discussed below.

TABLE 4 Rounded Scalar Competitive Scalar Competitive Value Index ValueIndex 7.121 0.95 7.1 0.95 6.879 0.85 6.9 0.85 5.432 0.75 5.4 0.75 5.1290.65 5.1 0.65 4.675 0.55 4.7 0.55 3.419 0.40 3.4 0.25 3.419 0.40 3.40.25 3.418 0.25 3.4 0.25 3.417 0.15 3.4 0.25 3.412 0.05 3.4 0.25

In the first column of TABLE 4, scalar values corresponding toattributes of products are listed. As shown, many of the scalar valuestoward the bottom of the list are substantially the same (i.e., 3.419,3.418, etc.) and their numeric differences in their scalar values is notsignificant in actual products. However, as shown in the second column,corresponding competitive index calculated using these scalar valuesshow that these scalar values toward the bottom of the list are givensubstantially different competitive indexes which range from 0.40 to0.05. This is due to the fact that the scale is too granular withpercentile ranges being very narrow. Such disparity in the competitiveindexes based on minute differences in the scalar value is misleading,because as a practical matter, the scalar values are substantially thesame. To prevent such erroneous calculation of competitive indexes, thescalar values are de-granularized, for instance by rounding, as shown inthe third column of TABLE 4. The corresponding competitive indexcalculated using these rounded scalar values of the third column ofTABLE 4 show that the scalar values toward the bottom of the list aregiven the same competitive index of 0.25 which more accuratelyrepresents the fact that these products are substantially the same withrespect to this particular attribute. In the above manner, the ratingsystem 10 in accordance with the present embodiment, may be adapted toautomatically round the scalar values to ensure that the percentileranges are reasonable in size.

In accordance with one embodiment of the present invention, the ratingsystem 10 includes a product rating module 22 that rates each productbased on the determined competitive index. For instance, the ratingsystem 10 may rate the plural products of a product category based onone or more attributes which may be requested by a consumer, an editor,an administrator, or any other user, collectively referred to herein asusers. In other words, the attributes to be considered by the ratingsystem 10 may be determined by the user of the system. Alternatively, orin addition, the user may be allowed apply a weighting to the importanceof one or more of the attributes upon which the rating is based. Forinstance, the user may be allowed to designate that the rating ofdigital camera should be based on the number of pixels and the type ofview screen provided, the number of pixels being weighted at 70% of therating and the type of view screen being less important and weighted at30%.

Alternatively, the user may be allowed to select a limited number oftypical use scenarios which weigh the importance levels of eachattribute differently. For instance, referring again to the digitalcamera example, a selection by the user indicating “outdoor sightseeingphotography” scenario would raise the importance level of “zoom”attribute and re-rank the products accordingly. Thus, in the abovedescribed manner, the product rating module 22 may be adapted to ratethe plural products based on the competitive index and the input fromthe user. Of course, the present invention is especially valuable toconsumers in assisting a purchase decision. Consequently, whereas thediscussions below refer to a consumer, it should also be understood thatan editor, an administrator, or any other user are implicitly referredto as well.

In accordance with one preferred embodiment of the present invention,the product rating module 22 of the rating system 10 is further adaptedto rate the products of a product category based on value the productsoffer to the consumer. As previously noted, the plurality of attributesthat is used to rate the products of a category preferably includes theprice of each of the plural products. This attribute of price allows theproducts to be rated based on the value each product offers to theconsumers. For example, the digital cameras may be ranked based on thenumber of pixels provided relative to the camera's price.

If a price of a product is not available for some reason, an estimatedstreet price may be manually provided to the rating system 10. Since newproducts debut with very few, or no, actual prices available, theanticipated street price may be provided to the rating system 10. Thisability to manually provide prices allows determination of thecompetitive index as well as the value index in the manner discussedbelow for new products as well. Of course, as actual prices becomeavailable for the particular product, the actual prices can be usedinstead of the estimated street price or the anticipated street price.In this regard, actual prices may be used in conjunction with theestimated street price or the anticipated street price by averaging themtogether, at least until a predetermined number of actual prices areavailable for use. For example, if an anticipated street price isinitially set at $500, and then the first merchant price comes in at$600, then both prices are used by averaging them together to derive an“estimated street price” of $550. However when more than a predeterminednumber of merchant prices are found, for instance, three merchants, theanticipated street price is no longer used and the actual prices can beused instead. If, in this example, all three merchants priced theproduct at $600, the price used is $600.

In accordance with the illustrated embodiment, the rating system 10further includes a price offset module 24 that determines price offsetof each product based on an average price of the plural products in thecategory. The price offset module 24 also apportions the price offset ofeach product to one or more attribute associated with the category ofproduct. Once the price offsets are determined and apportioned to theattribute(s), attribute-based price-differentials for each product areeffectively derived. In addition, to prevent skewing of the averageprice data, a predetermined number of the highest and/or the lowestprices of each product may be discarded in determining the average priceif the highest and/or the lowest prices are more than a certain numberof standard deviations away from the average.

Referring again to the digital camera example, if a digital camera costs$120 dollars more than the average cost for a digital camera, the $120premium may be apportioned to various attributes of the digital camerathat are above average in terms of the competitive index. In thisexample, the digital camera may have competitive index of 0.7 for theattribute of the number of pixels, and a competitive index of 0.6 forthe attribute of the type of view screen provided. In other words, thedigital camera has a competitive index 0.2 above average (i.e.0.7-0.5=0.2) for the number of pixels, and has a competitive index 0.1above average (i.e. 0.6-0.5=0.1) for the type of view screen. The priceoffset may be apportioned between these two attributes proportionately.In particular, $80 of the price offset (i.e. ⅔ of $120) may beapportioned to the attribute of number of pixels, while $40 of the priceoffset (i.e. ⅓ of $120) may be apportioned to the attribute of the typeof view screen. In addition, it should be noted that price offset may bea negative number as well for those products that cost less than theaverage cost. Such negative price offsets may be apportioned in asimilar manner. Again, these numbers and attributes are provided asexamples only and different number of attributes may be used in theexample of the digital camera, and other attributes used for otherproduct categories.

In addition, the price offset module 24 may also be used to correlatethe apportioned price offsets to increments of the competitive index.The correlation of the price offsets to increments of the competitiveindex may be attained by distributing the price offset in proportion tothe difference in (i.e. increments of) the competitive index. In otherwords, once the price offsets are determined for each product andapportioned, they are averaged together across all products for eachattribute. This effectively yields the average unit ofprice-per-increment of competitive index for each attribute. Forexample, each 0.01 increment of competitive index for the attribute ofnumber of pixels in a digital camera may be worth $12.80. Stated inanother manner, if a digital camera is better than average (above 0.50)in its number of pixel competitive index, it will be worth an additional$12.80 for every 0.01 competitive index that is above 0.50. If a digitalcamera is worse than average (below 0.50) in its number of pixelcompetitive index, it will be worth $12.80 less for every 0.01competitive index that is below 0.50. Of course, the above describedexample is merely provided for clarity. In addition, in otherembodiments, the correlation may be made in another manner and the priceoffset need not be proportional to the difference in the increment ofthe competitive index. In this regard, a non-linear correlation may bemade.

In accordance with the illustrated embodiment, the rating system 10further includes a valuation module 26 that determines a theoreticalvalue price of each product based on the correlated apportioned pricedoffsets as determined by the price offset module 24 described above. Asreferred to herein, the “theoretical value price” is the theoreticalmonetary value (e.g. in the U.S., the dollar value) of the product basedon its attributes. Because the unit of price-per-increment ofcompetitive index for each attribute is known, a theoretical value pricefor each product of a product category may be calculated. In the presentexample, by correlating the apportioned price offsets to each incrementof competitive index for each attribute of the digital camera using themethod described above, a theoretical value price of each digital cameracan be determined by the rating system 10.

In one embodiment, the theoretical value price of each product may bedetermined by adding the apportioned price offsets for each of theattributes of a product to the average price of all digital cameras. Inother words, in the example of digital cameras, the prices correspondingto each attribute for each of the digital cameras is determined usingthe competitive index and the correlated apportioned price offsets, i.e.the unit of price-per-increment of competitive index. The prices offsetscorresponding to all of the attributes of a digital camera are added tothe average price of all the digital cameras. In this regard, it shouldbe remembered that the price offsets corresponding to each attribute ofa particular product may be a negative value if the attribute of aparticular product has a competitive index below 0.5, the negative valuereducing the theoretical value price. Again, in the present example ofdigital cameras, such attributes may include optical and digital zoom,pixel size, presence, type and size of a view screen, flash capacity,memory capacity, etc. The final sum attained by adding all the priceoffsets associated with each attribute for each of the digital camerasto the average price of digital cameras provides the theoretical valueprice for each of the digital cameras price which is the price thedigital product should be worth in the market, i.e. its fair marketvalue. Of course, this theoretical value price may be higher or lowerthan the actual street price of the product.

The product rating module 22 may then be used to rate each of the pluralproducts based on the product's street price and its theoretical valueprice as determined by the valuation module 26 in the manner describedabove. A value index may be assigned based on the ratio or otherfunction of the calculated theoretical value price and the actual streetprice to thereby rate the value of the product. The value index may bederived by spreading any differential between the value price and thestreet price across a scale, such as a 1-10 scale. For example, for anexact match of the theoretical value price and the actual street price,a value index of 5.0 may be used. If the theoretical value price ishigher than the actual street price, this would indicate that theparticular product provides better value to customers and may beassigned a higher value index such as 7.0, etc. Of course, anyappropriate method may be used to provide a scale based on the actualproduct price and the theoretical value price as determined by thevaluation module 26. In addition, the rating of the plural productsbased on the value index may be sequenced in descending or ascendingorder to facilitate review of the product ratings.

As previously noted, the rating system 10 in the illustrated embodimentmay be implemented using a computational device such as a server and isconnected to network 14, for instance, the Internet. This allows thedetermined competitive index, the value index, and/or the sequencedproduct ratings to be published so that consumers can remotely accessthe rating system 10 and obtain the published information. In addition,such implementation of the rating system 10 allows the above describedprocess for rating plural products to be periodically or continuallyrepeated to ensure timeliness and accuracy of the ratings provided bythe rating system. In this regard, a script, i.e., a job that runsnightly, weekly, etc., may be used together with a mechanism (not shown)supplied to control its schedule. In addition, such repetition of ratingthe plural products may also be made on an on-demand basis. Moreover,the previous valid rating of a particular product may be stored and usedif, for some reason, a new rating cannot be determined.

Additional features and functions may also be provided in the ratingsystem 10 in accordance with various embodiments of the presentinvention. For instance, the product rating module 22 of the illustratedembodiment may be further adapted to monitor the ratings of eachproduct. If the rating of a particular product changes at least apredetermined amount, for instance, changes by a 2.5 value index, theproduct rating module 22 may be adapted to generate a notification ofsuch a change to an administrator and/or consumer(s). The notificationmay be an e-mail message distributed to members of a subscriber list.Alternatively or in addition thereto, a report may be sent every timethe value index is recalculated and published, the report identifyingproducts in which the value index has changed, the previous value indexand the new value index for those products, and the amount of change.The report may also group the products by major category and sort theproducts by descending order of the amount of change. Such disseminationof changes to the value index may be very valuable to consumers that areinterested in particular products or particular category of productssince dramatic change in the value index indicates a major price changethat can suddenly make a particular product an outstanding value.

To protect against publishing erroneous ratings, the rating module 22may withhold publication of the ratings if more than a predeterminedpercentage of products in a particular product category have their valueindexes change by more then a predetermined percentage. This protectsagainst corrupt data feeds which may occur, for example, if a merchantmaintains a price list where all the prices were corrupted. In such aninstance, the rating system 10 may be adapted to withhold publication ofthe ratings and send an alert to the administrator so that the changesin the value indexes may be validated.

In addition, the rating module 22 of the rating system 10 may optionallybe adapted to generate a product diagnostic report which shows variousadditional detailed information revealing the details of the competitiveindex, value index and/or rating for any product according to a desiredsearch criteria. In this regard, data visualizations and graphs may begenerated to facilitate comprehension of the presented information.Historical data for each product may be archived to enable the creationof history graphs for any product or class of products. For example, agraph illustrating the ratings of a product may be generated and shownas a rolling average of a predetermined time duration such as 14 days.The report requester may also be allowed to set various parameters forthe historical data, such as the time duration the data should reflect.For instance, the time duration may be set from 1 to 365 days.

Further, additional features and functions may also be provided in therating system 10 in accordance with various embodiments of the presentinvention. For instance, the price offset module 24 may be furtheradapted to calculate a correlation reliability value to ensure that theratings of the products by the rating system 10 corresponds to realityin the marketplace. For example, a correlation reliability value may beindicative of correlation between a product attribute and price offsetapportioned to the product attribute. Alternatively, or in additionthereto, the correlation reliability value may be, for example, aCronbach alpha reliability value that is indicative of the correlationamong the competitive indexes of the products for the attributes. If theCronbach alpha reliability value tended to correlate among thecompetitive indexes of the products, the correlation is strong and therating will correspondingly be reliable. Cronbach alpha reliabilityvalue can be used to measure correlation due to the fact thatmanufacturers tend to upgrade various features of their products intandem with one another. For instance, in the example of digitalcameras, manufacturers generally will not offer a digital camera with alarge 6 megapixels resolution and a limited 2× zoom. When competitiveindexes tend to rise and fall together over various products in theproduct category, the reliability of the correlation is confirmed andthe ratings will correspondingly be reliable. Of course, other types ofcorrelation reliability values may be used in other embodiments. Thedetails of calculating correlation reliability values such as Cronbachalpha reliability values are known in the art and thus, are omittedherein.

If the correlation is found to be below a predetermined level, the priceoffset module 24 may be further adapted to disregard the productattribute in determining the competitive index. When the competitiveindex of a particular attribute changes erratically when compared to theother attributes of a product category, for example, the competitiveindex is often high when others are low and vice versa, the Cronbachalpha reliability value is lowered. The lowering of the Cronbach alphareliability value indicates that the correlation is weak. Again, suchproduct attributes that are found to have a correlation below apredetermined level may be disregard by the price offset module 24.

Moreover, the price offset module 24 may also be adapted to generate awarning such as an e-mail warning, if the correlation is less than apredetermined level. In certain cases, a low item correlation for aparticular product attribute may be tolerated if the attribute is veryimportant and does not effect the overall accuracy of the ratings. Forexample, as applied to digital cameras, the attribute of optical zoom isvery important and thus, would preferably not be discarded. In thisregard, a Boolean flag may be set for each attribute to allowdetermination of whether it is to be included in the calculation of thevalue index or not, thereby allowing exclusion of a particularattribute. Whenever an attribute is excluded, either manually orautomatically, notifications such as an e-mail may be automaticallygenerated by the rating system 10 to administrators and other interestedusers.

In accordance with the illustrated embodiment, the rating system 10 mayalso optionally be provided with a threshold module 28 that assigns animportance level to the attributes, and sets a corresponding thresholdto the importance level which sets a maximum number of attributes thatcan be absent from a product at the particular importance level for theproduct to be used in determining the incremental competitive index bythe indexing module 20. Thresholds may be expressed as “importance:number of attributes missing”. For example, “0.90:0” would mean that aproduct cannot be missing any attributes of importance 90. In a similarmanner, “0.80:1” would mean the product can be missing at most oneattribute with importance 80, and “0.70:2” would mean the product can bemissing no more than two attributes of importance 70, in order tosatisfy having an “essential” combination of attributes. This ability toset importance levels and thresholds to attributes is useful insituations where product information gathered by the identificationmodule 16 of the rating system 10 is incomplete with respect to one ormore attributes for one or more products. This may occur due to the factthat different manufacturers do not publish identical specificationsregarding their products. Thus, this feature can be readily used toensure integrity of the competitive index, the value index, and theratings derived from such specifications.

In the above regard, products that do not have a particular attributeinformation may still be rated by the rating system 10 by assigning 0.50competitive index as a default value with respect to the particularattribute of the product. This allows rating of products for whichinformation gathered by the identification module 16 is incomplete forsome reason. As can be appreciated, by incorporating the above featureof importance levels and thresholds, the rating system 10 may beoperated to absolutely require very important attributes to be presentbefore being rated. For instance, with respect to digital cameras,information regarding resolution is very important and thus, thecorresponding importance level and threshold are set so that resolutioninformation must be present for the product to be ranked.

Furthermore, additional factors may also optionally be considered duringthe process of ranking the plural products of a product category by theranking system 10. These additional factors may include user opinions,brand quality scores, brand affinity ratings, customer support levels,etc. In this regard, an optional provision may be made to encompassbrand consideration in rating of products in a product category. Thismay be implemented by assigning a weight to each brand that haveproducts ranked in the product category. A global brand weight may beused by default for every product category for that brand. However, thisglobal brand weight may be optionally overridden for a particularproduct category. For instance, an electronics manufacturer may be givena global brand weight with respect to audio equipment, another brandweight for digital cameras, and yet another brand weight for computerequipment. The assignment of brand weight may be based on numerousfactors such as reputation, reliability, warranty, customer support,etc.

Moreover, because the ranking system 10 in accordance with theillustrated embodiment is connected to a network 14, an optionalprovision may be made to allow manufacturers of rated products to alterone or more attribute of their products to see how such alterationsaffect the rating of the product. For example, a manufacturer of adigital camera may be allowed to alter attributes of memory size, numberof pixels, price, etc. of their product(s) to see their impact on theproduct's rating. Of course, these hypothetical ratings are not foractual products, and hence, are not published for consumers to view.

It should now be evident from the discussion above that the presentinvention also provides a method for rating each of plural products asshown in the schematic diagram 100 of FIG. 2 that illustrates oneembodiment of the method. As shown, the method includes step 110 whereplurality of attributes associated with a category of product isidentified. In step 120, a scalar structure is applied for eachattribute to provide scalar value of each attribute for each of theplural products. In step 130, an incremental competitive index isdetermined for each attribute of each product based on the scalar valueof each attribute applied in step 120 and the number of products havingthe scalar value. Each product is then rated in step 140 based on thecompetitive index determined in step 130.

In accordance with another embodiment, the present invention alsoprovides another method for rating plural products as shown in theschematic diagram 200 of FIG. 3. In accordance with the method of FIG.3, a plurality of attributes associated with a category of product areidentified in step 210, the plurality of attributes preferably includingprice for each of the plural products. A scalar structure for eachattribute is applied in step 220 to provide scalar value of eachattribute for each of the plural products. In step 230, an incrementalindex is determined for each attribute of each product based on thescalar value of each attribute as applied in step 220. Preferably, theincremental index is a competitive index which is based on number ofproducts having the scalar value. However, the incremental index mayalso be based on a percentile rank.

In accordance with the present method, a price offset of each product,which is based on an average price of the plural products in thecategory, is determined in step 240 and apportioned to one or moreattribute associated with the product category in step 250. Theapportioned price offsets are then correlated to increments ofincremental index in step 260. A theoretical value price of each productis then determined in step 270 based on the correlated apportioned priceoffsets, for instance, by adding the price offsets of each attribute ofeach product to the average price of the products in the productcategory. In step 280, the plural products are then rated based onactual product price and the determined theoretical value price. Theratings of the plural products may then be published in step 290.

As can also be appreciated, additional steps may also be provided in thepresent method of FIG. 3. For instance, the step 230 for determiningincremental index for each attribute may also include step 232 in whichpercentile rank of each scalar value is calculated, step 234 in which apercntile rank range which each scalar value spans is calculated, andstep 236 in which a maximum percentile rank and a minimum percentilerank of the calculated percentile rank range are praveraging of themaximum percentile rank and the minimum percentile rank together and/orsequencing the scalar values of each attribute for the plural products.

Furthermore, additional optional steps may also be provided inaccordance with various embodiments of the present method. For instance,in step 250, the apportionment of the price offset of each product toone or more attribute may be based on the determined incremental indexof each attribute for each product. Importance levels with correspondingthresholds may be assigned to the attributes as described previously toset maximum number of attributes that can be absent from a product atthe importance level for the product to be subjected to step 230 inwhich the incremental index is determined.

Moreover, a correlation reliability value may be calculated to ensureintegrity of the ratings. The correlation reliability value may monitorcorrelation between a product attribute and price offset apportioned tothe product attribute. Alternatively, Cronbach alpha reliability valueor other correlation reliability value may be used. In this regard, awarning may be generated if the correlation is less than a predeterminedlevel. Additionally, a notification may be generated if a rating of aproduct changes a predetermined amount.

Lastly, as previously noted, the present invention may be implementedusing hardware and/or software. Therefore, it should also be apparentthat another aspect of the present invention is a computer readablemedium for rating plural products having instructions for identifying aplurality of attributes associated with a category of product, applyinga scalar structure for each attribute to provide scalar value of eachattribute for each of said plural products, determining a competitiveindex for each attribute of each product based on said scalar value ofeach attribute and a number of products having said scalar value, andrating each product based on said determined competitive indexes. Inthis regard, it should also be apparent that the computer readablemedium may also be provided with additional instructions forimplementing the method and system as more fully described above.

While various embodiments in accordance with the present invention havebeen shown and described, it is understood that the invention is notlimited thereto. The present invention may be changed, modified andfurther applied by those skilled in the art. Therefore, this inventionis not limited to the detail shown and described previously, but alsoincludes all such changes and modifications as defined by the appendedclaims and legal equivalents.

I/we claim:
 1. A method implemented by at least one computing device forenhancing a database of records corresponding to plural items, each itembeing assigned to a category, each item having a corresponding itemrecord recorded in the database, each item record including a set ofattributes that represent features of the item, each attribute beingassigned a corresponding scalar value that represents a state of thecorresponding attribute, the method comprising: retrieving from thedatabase, by at least one computing device, the sets of attributes andthe corresponding scalar values for each attribute; determining, by atleast one computing device, a competitive index for one or more of theattributes based on the corresponding scalar values, wherein thecompetitive index is determined by, for each of the attributes;collecting the corresponding scalar values from plural sets ofattributes corresponding to plural items to create a set of scalarvalues for the attribute; calculating a percentile rank of each scalarvalue in the set of scalar values scalar value, wherein the maximumpercentile rank and the minimum percentile rank are not the same;calculating a numerical value of a percentile rank range of each scalarvalue; determining a maximum percentile rank range and a minimumpercentile rank range of the percentile rank ranges; for each scalarvalue, calculating an average of the numerical value of the maximumpercentile rank range and the minimum percentile rank range to therebyobtain the competitive index; and storing, in a database, thecompetitive index for each attribute of a corresponding item as anenhanced attribute value in association with the attribute to therebycreate an enhanced item record for the item, whereby the enhance itemrecord can be used to evaluate the item with respect to other items by acomputing device in a more accurate manner.
 2. The method of claim 1,further including the step of assigning an importance level to at leastone attribute, and setting a corresponding threshold to the importancelevel which indicates a maximum number of attributes that can be absentfrom an item at said importance level for the attribute valuescorresponding to the item to be subjected to said step of determining acompetitive index.
 3. The method of claim 1, further comprising:calculating a correlation reliability value for at least one of theenhanced attribute values, the correlation reliability value beingindicative of a correlation between the at least one of the enhancedattribute values and a price offset corresponding to the correspondingattribute; and storing the correlation reliability value in associationwith the enhanced data record to thereby allow more accurate pricing ofthe corresponding item to be automatically determined based on theenhanced data record.
 4. The method of claim 3, further including thestep of generating a warning if said correlation reliability value isless than a predetermined level.
 5. The method of claim 3, furtherincluding the step of disregarding an attribute value in determining thecompetitive index if the corresponding correlation reliability value isless than a predetermined level.
 6. The method of claim 1, wherein thedetermining a competitive index further comprises rounding at least someof the scalar values to adjust numerical value of a percentile rankrange of each scalar value to be at least a predetermined minimum value.7. The method of claim 1, further comprising rating the items based onthe enhanced data records.
 8. The method of claim 1, further comprisingassigning a price value the items based on the enhanced data records. 9.The method of claim 8, wherein the assigning comprises determining aprice offset of each item based on an average price of products in thesame category as the item.
 10. A system for enhancing a database ofrecords corresponding to plural items, each item being assigned to acategory, each item having a corresponding item record recorded in thedatabase, each item record including a set of attributes that representfeatures of the item, each attribute being assigned a correspondingscalar value that represents a state of the corresponding attribute, thesystem comprising: at least one computer processor; and at least onememory device operatively coupled to the at least one computer processorand storing computer readable instructions which, when executed by theat least one computer processor, cause the at least one computerprocessor to: retrieve from the database the sets of attributes and thecorresponding scalar values for each attribute; determine a competitiveindex for one or more of the attributes based on the correspondingscalar values, wherein the competitive index is determined by, for eachof the attributes; collecting the corresponding scalar values fromplural sets of attributes corresponding to plural items to create a setof scalar values for the attribute; calculating a percentile rank ofeach scalar value in the set of scalar values scalar value, wherein themaximum percentile rank and the minimum percentile rank are not thesame; calculating a numerical value of a percentile rank range of eachscalar value; determining a maximum percentile rank range and a minimumpercentile rank range of the percentile rank ranges; for each scalarvalue, calculating an average of the numerical value of the maximumpercentile rank range and the minimum percentile rank range to therebyobtain the competitive index; and storing, in a database, thecompetitive index for each attribute of a corresponding item as anenhanced attribute value in association with the attribute to therebycreate an enhanced item record for the item, whereby the enhance itemrecord can be used to evaluate the item with respect to other items by acomputing device in a more accurate manner.
 11. The system of claim 10,wherein the instructions further cause the at least one computerprocessor to assign an importance level to at least one attribute, andset a corresponding threshold to the importance level which indicates amaximum number of attributes that can be absent from an item at saidimportance level for the attribute values corresponding to the item tobe subjected to determining a competitive index.
 12. The system of claim1, further wherein the instructions further cause the at least onecomputer processor to: calculate a correlation reliability value for atleast one of the enhanced attribute values, the correlation reliabilityvalue being indicative of a correlation between the at least one of theenhanced attribute values and a price offset corresponding to thecorresponding attribute; and store the correlation reliability value inassociation with the enhanced data record to thereby allow more accuratepricing of the corresponding item to be automatically determined basedon the enhanced data record.
 13. The system of claim 12, wherein theinstructions further cause the at least one computer processor togenerate a warning if said correlation reliability value is less than apredetermined level.
 14. The system of claim 12, wherein theinstructions further cause the at least one computer processor todisregard an attribute value in determining the competitive index if thecorresponding correlation reliability value is less than a predeterminedlevel.
 15. The system of claim 10, wherein the determining a competitiveindex further comprises rounding at least some of the scalar values toadjust numerical value of a percentile rank range of each scalar valueto be at least a predetermined minimum value.
 16. The system of claim10, wherein the instructions further cause the at least one computerprocessor to rate the items based on the enhanced data records.
 17. Thesystem of claim 10, wherein the instructions further cause the at leastone computer processor to assign a price value the items based on theenhanced data records.
 18. The system of claim 17, wherein the assigningcomprises determining a price offset of each item based on an averageprice of products in the same category as the item.